Anyone can setup a Grapevine Slack bot and have it respond to and optionally proactively answer questions that require company context. Here’s a demo video with examples: https://youtu.be/_nrfbZzvxU8
We built Grapevine because we were interested in a ChatGPT that fully understands your company. We'd tried many of the existing tools (including expensive enterprise ones), but while they were good at answering “what is X team’s Q4 goal,” they weren’t good at the day-to-day questions that actually blocked people.
So, our founders and early engineers created a set of 100+ representative questions, from hard technical questions to company-specific knowledge questions. At first, the state-of-the-art “enterprise search” products were getting about 50% of them correct, and our in-house system was getting 35%. But as we solved details in data processing, search algorithm, and more, we eventually achieved 85%. (For reference, the best human score our founders got was 70%)
It’s changed the way we work: popular engineering channels that have 5+ questions / day are fully answered proactively by AI, and people across departments go to the bot first for bug reports, incidents, and support tickets. Dozens of our beta customers have been consistently surprised by the quality of the answers, too.
Security is obviously super important for a product like this. We will never train on your data. In addition, your data is encrypted at rest, in an isolated database from other customers, and the system is SOC 2 compliant with regularly scheduled pen tests. We built it to Gather’s (https://gather.town/) SOC 2 Type II standards - that’s the original virtual office product we launched (and still maintain) out of YC, but we’ve since pivoted to Grapevine.
We put a lot of effort into making Grapevine easy to set up. You can try it now, for free, at https://getgrapevine.ai
Do not assume that companies are willing to put ALL of their intellectual property into your hands. Even if you would not be some startup where any sysadmin could steal and sell my data any time without you even noticing it, you will get hacked just like everyone else that stores interesting data. The data you have access to is absolutely perfect for the global data blackmailing gangs. As soon as you are successful, you will have every black hat hacker and their dog knocking on your doors.
To be clear: I am looking at this from a CEO perspective, not a "I will play with it in my spare time" nerd one.
Not looking to spend millions but a couple thousand are alright. TIA
Businesses that would be willing to pay (a lot) for such a benefit often will be very conservative. In Germany the majority of medium sized businesses using SAP for example still refuse to be moved to SAP's cloud instead of on-premise.
C-Level types typically are not worried putting their email credentials etc into Outlook cloud and getting hacked this way. They are used to "everything is in the cloud". However, as soon as you mention, depending on the type of business "patents", "sales contacts", "production plans" C's will change their mind.
In Germany, where I am originally come from, all of these businesses are worried about their trade secrets to end up in China, and rightly so.
As self-hosting is very complex you could either make good money with consulting (but this means setting up tech teams in all target markets around the globe, using actual competent humans), or by selling it as a plug&play appliance. With that appliance simply being a rack server with a suitable GPU installed.
And again, for your business strategy the long-term risk of pretty much everyone trying to hack you on a daily basis appears too high to me. You might not have on your radar how serious industry spionage is. You will definitely have a fake utility company worker coming into your offices, trying to plug in a USB keylogger into some PC while nobody is looking.
As an example, proven strategy: Find targets internet uplink. Cut it. Customer calls ISP for help. You then send a fake ISP technician that arrives before the real one does. You put a data exfiltration dongle between the modem and the LAN. You then fix the cut outdoor line. Customer is happy that you have fixed it. Later the actual ISP guy arrives. Everyone will be a bit confused that the problem was already fixed, but then agree that it's probably just the ISP once again having screwed up their resource management. Works pretty much every time.
a) Due to privacy laws, no European country would right now be allowed to use your service. The data your customers wants to index will always contain stuff that allows to identify a human, and once you are there it's basically "game over" for handing over data to a third party provider like you.
b) My organization is tiny. But we are in a sector were we must be ultra paranoid when it comes to security. We do not use a single external service whatsoever, everything is self-hosted. I would love to be able to AI-index all of our collected knowledge and would pay for the value this provides. So far have been unable to find any plug & play solution. Then open source nature you have mentioned is important so that your system security can be be validated, but in the end I would rather want to pay for it being plug&play AND on-premise AND open source.
Also willing to buy.
People can usually tell if an answer isn't helpful, but not always that it isn't accurate. Depending on the context, 85% accurate might not be good enough.
Instead of using the lower bound, wouldn't it make more sense to say "85% of the 95% accurate answers are helpful"? Or perhaps "95% of the 85% helpful answers are accurate"?
In both cases, the number for "answers that are both helpful and accurate" is lower than 85%.
I get that's a big ask from a startup. If it helps, we are a company that's been around for 4+ years and have built a work tool (https://gather.town) used for 100k+ people for their daily work, Sequoia-backed, are SOC II certified, and go way beyond that for the security considerations for this product.
However, it didn't reach the growth trajectory we needed, so a majority of the company will be working on Grapevine + new products instead.
We've still been searching for a proper replacement for go-karting. Our team greatly enjoyed that little mini game.
A thought for any lurking vibe-coders.
do you have a very strong opinion about how companies should work?
"No"
Okay, does Dario Amodei? He thinks more than half the workforce should "just" be replaced. That's a strong opinion! Do you see what I am saying?
With the company GPT, we want to tackle things like: 1.) having to answer a repeated question from a colleague, 2.) answering questions to coworkers that are purely informational, and eventually 3.) things like standup updates, written updates to leadership on status, etc.
I think human interaction at work is one of the most valuable experiences if you're lucky enough to have good colleagues and interesting work. But I think they should almost entirely be around creativity, decision-making, debate, etc. rather than sharing information that exists elsewhere.
It's cool feature but is it not the given and default feature of any RAG based LLM to provide citations based on the documents chunking mechanism?
What type of businesses are you targeting?
Our sense is that ~70% knowledge companies at large still don't have a custom GPT yet, and that of the people who do, our system can be more performant because we're spending more effort than their internal team is. There's a lot of details we've solved on data ingestion and search algo that improved our accuracy dramatically, and things breadth of data connectors is the kind of thing that is expensive for an internal team but worth it if you're providing the service at large.
Not sure what you mean by "data seems to be stored outside of the customers control," but fortunately I think many SaaS apps that were trying to lock down customer data from themselves are walking that back a little bit.
[1] https://platform.openai.com/docs/guides/your-data#zero-data-...
2020-2022: We built https://gather.town, which during COVID blew up across every use-case possible: conferences, birthday parties, weddings, universities. It was a good business during COVID but eventually started to shrink.
2022-2025: We built Gather for remote workers, which was a long grind into in Audio/Video, performance, and making a game-interface that was good for work but replicated the parts of in-person work people enjoyed. It's a decent business, but didn't match our ambitions with how we wanted to change work for the better.
2025+: We have lots of ideas for how we can make work a lot better with AI. The general theme is, "can we make work as fun as a video game?" Idea being: video games are super similar to work at its core, and AI can both 1.) dramatically change how people need to spend their days, and 2.) help you "game design" someone's work day.
The Grapevine system is the first tablestakes layer people need to have for us to build the products we're excited about. Surprisingly, "company context" was not as good as we thought despite it being such an obvious, big business opportunity. So while I agree it's "basic," it does seem necessary, and is also not the full-scale of what we want to achieve still :)
There is the ChatGPT product, operated by OpenAI, Inc, which you can access via their web site or their API. OpenAI does publish gpt-oss as an open-weights model. I suppose you could argue that gpt-oss is "a ChatGPT," though I'd normally think of it as "a large language model." Much like Claude, DeepSeek, Qwen and so on are other large language models.
I was recently trying to tackle the same problem (@howie.systems). The hardest 2 problems we had to face were ACL and large files (and large volumes).
How did you solve the ACL part? I worked with a customer that had 200k pdf/images/dwg files on SharePoint and other 1M on samba. It took like a week to sync it all and keep tabs on the access rights of each employee.
How did you solve unpredictable large files: a pdf 2000pages, maybe some A0 in the mix. Or some 4GB power point presentations?
PS: great fan of gather. PPS: say hi to Clinton from me (amy.app) if he is still around. He was our mentor back in New Zealand at the flux accelerator (2016)
Forgive my cynicism, but $2 says they simply didn’t.
(Additionally, there are a lot of details that do make a big difference in data processing / search algo too, which have taken our own internal accuracy on hard questions from 30% => 80%+)
I can't speculate exactly on the work that other companies have done, but my guess is we were way more focused on the type of questions people actually ask to each other. We know there's still a lot more you can do to continue to improve it, and so it's up to other folks if they do it too.
Lastly, a few ways we want to be distinguished from all the other offerings are: 1) super easy to setup, 2.) very developer friendly
